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Abstract To address the issue of low accuracy in soft sensor modeling of key variables caused by multi-variable coupling and parameter sensitivity in complex processes, this paper introduces a TSK-type-based self-evolving compensatory interval type-2 fuzzy Long short-term memory (LSTM) neural network (TSECIT2FNN-LSTM) soft sensor model. The proposed TSECIT2FNN-LSTM integrates the LSTM neural network with the interval type-2 fuzzy inference system to address long-term dependencies in sequence data by utilizing the gate mechanism of the LSTM neural network. The TSECIT2FNN-LSTM structure learning algorithm uses the firing strength of the network rule antecedent to decide whether to generate new rules to improve the rationality of the network structure. TSECIT2FNN-LSTM parameter learning utilizes the gradient descent method to optimize network parameters. However, unlike other interval type-2 fuzzy neural network gradient calculation processes, the error term in the LSTM node parameter gradient of TSECIT2FNN-LSTM is propagated backwards in the time dimension. Additionally, the error term is simultaneously transferred to the upper layer network to enhance network prediction accuracy and memory capabilities. The TSECIT2FNN-LSTM soft sensor model is utilized to predict the alcohol concentration in wine and the nitrogen oxide emission in gas turbines. Experimental results demonstrate that the proposed TSECIT2FNN-LSTM soft sensing model achieves higher prediction accuracy compared to other models.

Abstract In recent years, the application of real scene 3D technology has become widespread in urban planning and cultural heritage protection. However, there has been relatively little attention paid to the construction of real scene 3D models for special natural landscapes such as caves. Given the global distribution of karst topography and the large number of naturally developed caves with diverse types, unique landscape styles, and significant scientific value, this paper enriches the research in this field. By combining ground-based and aerial remote sensing techniques, and based on 3D laser scanning and photogrammetry, we have successfully constructed a real scene 3D model of the internal structure of a karst cave with a precision better than 4 cm. Utilizing Unmanned Aerial Vehicle (UAV) oblique photography, we established a real scene 3D model of the external karst landform with a precision better than 2 cm. We also integrated the internal and external 3D models of the cave, developing a new, complete, and high-precision method for constructing real scene 3D models of karst cave landscapes. Furthermore, we proposed a method for texture reproduction in the dark environment inside the caves, enhancing the reproduction and visual appeal of the real interior. The establishment of high-precision real scene 3D models can not only serve as an effective tool for scientific research on caves but also, as replicas of the real world, play a crucial role in public dissemination and education, thereby enhancing public understanding of cave geological landscapes.

Abstract This study spanned 6 years and 4 generations, involving the progressive crossbreeding of South African Kalahari Goat (SK) and Guizhou Black Goat (GB) over three generations, followed by cross fixation F3 with F1 in the fourth generation, accompanied by the use of molecular markers technology to select a high fertility population, resulting in the creation of a hybrid goat, BKF4 (11/16 SK lineage and 5/16 GB lineage). A comparative evaluation of the BKF4 hybrid breed and its parental breeds was conducted. Reproductive and production parameters of GB, SK, and BKF4 goat groups were monitored, including lambing rate (LR), survival rate (SR), daily weight gain at 3 months of age (DWG), and adult body weight (ABW) (n = 110, 106, 112 per group). In addition, dressing percentage (DP) (n = 12 per group) and analyses of amino acids (n = 8, 6, 10 per group) and fatty acids (n = 6 per group) were conducted to evaluate meat quality indicators. Results: (1) Reproductive and production performance: The index of LR reached 199%, significantly higher than GB and SK (p ≤ 0.001), with a SR of 95.0%, markedly higher than SK (p ≤ 0.001); DWG was 276.5 g, ABW reached 56.6 kg and with a dressing percentage (DP) of 54.5%, they are significantly surpassing GB (p ≤ 0.001). (2) Regarding meat quality: pH45-value and crude protein content (CP) increased, while intramuscular fat content increased compared to GB and ash content decreased. The amino acid composition was similar to GB, but the taste was more similar to SK. However, there were some negative impacts on fatty acid composition and functionality. (3) PCA analysis revealed that: BKF4 exhibited superior meat quality compared to GB and SK, influenced by two key factors contributing 83.49% and 16.51% to the explained variance, respectively. The key factors affecting meat quality include intramuscular fat (IMF), nutrient index (NI), PUFAs/MUFAs, n-6FAs, and drip loss (DL).

Abstract Ubiquitin-like with PHD and RING finger domains 1 (UHRF1) is an epigenetic regulator that plays critical roles in tumours. However, the DNA methylation alteration patterns driven by UHRF1 and the related differentially expressed tumour-related genes remain unclear. In this study, a UHRF1-shRNA MCF-7 cell line was constructed, and whole-genome bisulfite sequencing and RNA sequencing were performed. The DNA methylation alteration landscape was elucidated, and DNA methylation-altered regions (DMRs) were found to be distributed in both gene bodies and adjacent regions. The DMRs were annotated and categorized into 488 hypermethylated/1696 hypomethylated promoters and 1149 hypermethylated/5501 hypomethylated gene bodies. Through an integrated analysis with the RNA sequencing data, 217 methylation-regulated upregulated genes and 288 downregulated genes were identified, and these genes were primarily enriched in nervous system development and cancer signalling pathways. Further analysis revealed 21 downregulated oncogenes and 15 upregulated TSGs. We also showed that UHRF1 silencing inhibited cell proliferation and migration and suppressed tumour growth in vivo. Our study suggested that UHRF1 and the oncogenes or TSGs it regulates might serve as biomarkers and targets for breast cancer treatment.

Abstract Collision-free path planning and task scheduling optimization in multi-region operations of autonomous agricultural robots present a complex coupled problem. In addition to considering task access sequences and collision-free path planning, multiple factors such as task priorities, terrain complexity of farmland, and robot energy consumption must be comprehensively addressed. This study aims to explore a hierarchical decoupling approach to tackle the challenges of multi-region path planning. Firstly, we conduct path planning based on the A* algorithm to traverse paths for all tasks and obtain multi-region connected paths. Throughout this process, factors such as path length, turning points, and corner angles are thoroughly considered, and a cost matrix is constructed for subsequent optimization processes. Secondly, we reformulate the multi-region path planning problem into a discrete optimization problem and employ genetic algorithms to optimize the task sequence, thus identifying the optimal task execution order under energy constraints. We finally validate the feasibility of the multi-task planning algorithm proposed by conducting experiments in an open environment, a narrow environment and a large-scale environment. Experimental results demonstrate the method's capability to find feasible collision-free and cost-optimal task access paths in diverse and complex multi-region planning scenarios.

Abstract Programmed Death Receptor 1 (PD-1) inhibitors, when combined with chemotherapy, have exhibited notable effectiveness in enhancing the survival outcomes of patients afflicted with advanced gastric cancer. However, it is important to acknowledge that not all patients derive substantial benefits from this therapeutic approach, highlighting the crucial necessity of identifying efficacious biomarkers to inform immunotherapy interventions. In this study, we sought to investigate the predictive utility of circulating tumor DNA (ctDNA) as a biomarker in a cohort of 30 patients diagnosed with advanced gastric cancer, all of whom underwent first-line treatment involving PD-1 inhibitor administration alongside chemotherapy. We procured peripheral blood samples both at baseline and following the completion of two treatment cycles. Additionally, baseline tissue specimens were collected for the purpose of genomic alteration assessment, employing both 47-gene and 737-gene next-generation sequencing panels for plasma and tumor tissue, respectively. We delineated a ctDNA response as the eradication of maximum variant allele frequencies relative to baseline levels. Notably, the objective response rate among individuals exhibiting a ctDNA response proved significantly superior in comparison to non-responders (P = 0.0073). Furthermore, patients who manifested a ctDNA response experienced markedly prolonged progression-free survival (PFS) and overall survival (OS) when juxtaposed with those devoid of a ctDNA response (median PFS: 15.6 vs. 6.0 months, P = 0.003; median OS: not reached [NR] vs. 9.0 months, P = 0.011). In summation, patients with advanced gastric cancer receiving first-line treatment with PD-1 inhibitors and chemotherapy, dynamic changes in ctDNA can serve as a potential biomarker for predicting treatment efficacy and long-term outcomes.

Abstract This study aimed to investigate impacts of Omicron infection on cancer patients in China. A retrospective study was conducted, including 347 cancer patients undergoing radiotherapy or chemoradiotherapy between July 2022 and March 2023. Three groups involved: 108 patients without SARS-CoV-2 infection (non-COVID-19 group), 102 patients beginning treatment 10 days after first SARS-CoV-2 infection (≥ 10 days COVID-19 group), and 137 patients beginning treatment less than 10 days after first SARS-CoV-2 infection (

Abstract Understanding water saturation levels in tight gas carbonate reservoirs is vital for optimizing hydrocarbon production and mitigating challenges such as reduced permeability due to water saturation (Sw) and pore throat blockages, given its critical role in managing capillary pressure in water drive mechanisms reservoirs. Traditional sediment characterization methods such as core analysis, are often costly, invasive, and lack comprehensive spatial information. In recent years, several classical machine learning models have been developed to address these shortcomings. Traditional machine learning methods utilized in reservoir characterization encounter various challenges, including the ability to capture intricate relationships, potential overfitting, and handling extensive, multi-dimensional datasets. Moreover, these methods often face difficulties in dealing with temporal dependencies and subtle patterns within geological formations, particularly evident in heterogeneous carbonate reservoirs. Consequently, despite technological advancements, enhancing the reliability, interpretability, and applicability of predictive models remains imperative for effectively characterizing tight gas carbonate reservoirs. This study employs a novel data-driven strategy to prediction of water saturation in tight gas reservoir powered by three recurrent neural network type deep/shallow learning algorithms—Gated Recurrent Unit (GRU), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), K-nearest neighbor (KNN) and Decision tree (DT)—customized to accurately forecast sequential sedimentary structure data. These models, optimized using Adam's optimizer algorithm, demonstrated impressive performance in predicting water saturation levels using conventional petrophysical data. Particularly, the GRU model stood out, achieving remarkable accuracy (an R-squared value of 0.9973) with minimal errors (RMSE of 0.0198) compared to LSTM, RNN, SVM, KNN and, DT algorithms, thus showcasing its proficiency in processing extensive datasets and effectively identifying patterns. By achieving unprecedented accuracy levels, this study not only enhances the understanding of sediment properties and fluid saturation dynamics but also offers practical implications for reservoir management and hydrocarbon exploration in complex geological settings. These insights pave the way for more reliable and efficient decision-making processes, thereby advancing the forefront of reservoir engineering and petroleum geoscience.

Abstract Clarifying the principles of proportioning optimization for brittle transparent rock-like specimens with differential fracture structures is crucial for the visualization study of the internal fracture and seepage evolution mechanisms in rock masses. This study, utilizing orthogonal experimental methods, uncovers the influence mechanisms, extents, and patterns by which the ratios of resin, hardener, and accelerator, along with the freezing duration, impact the mechanical characteristics of transparent rock-like specimens. Notably, it was observed that as the accelerator ratio and freezing time are increased, there’s a general decline in the uniaxial compressive strength, tensile strength, and elastic modulus of the specimens. In contrast, an increase in the hardener ratio initially leads to an enhancement in these mechanical properties, followed by a subsequent decrease. Under uniaxial compressive loading, the specimens exhibit four typical modes of failure: bursting failure, splitting failure, single inclined plane failure, and bulging failure. As the hardener and accelerator ratios increase, the mode of failure gradually shifts from bulging to bursting, with freezing time having a minor overall impact on the evolution of failure modes. The study proposes a method for inducing random three-dimensional closed fractures within the specimens and further clarifies the principles for optimizing the proportions of specimens with different fracture structures, such as intact, embedded regular, and random three-dimensional fractures. This research facilitates the in-depth application of transparent rock-like materials in various scenarios and provides theoretical guidance and technical support for visualizing the evolution of fracture and seepage characteristics within the fractured rock mass.

Abstract There are many factors that affect the compressive strength of concrete. The relationship between compressive strength and these factors is a complex nonlinear problem. Empirical formulas commonly used to predict the compressive strength of concrete are based on summarizing experimental data of several different mix proportions and curing periods, and their generality is poor. This article proposes an improved artificial bee colony algorithm (IABC) and a multilayer perceptron (MLP) coupled model for predicting the compressive strength of concrete. To address the shortcomings of the basic artificial bee colony algorithm, such as easily falling into local optima and slow convergence speed, this article introduces a Gaussian mutation operator into the basic artificial bee colony algorithm to optimize the initial honey source position and designs an MLP neural network model based on the improved artificial bee colony algorithm (IABC-MLP). Compared with traditional strength prediction models, the ABC-MLP model can better capture the nonlinear relationship of the compressive strength of concrete and achieve higher prediction accuracy when considering the compound effect of multiple factors. The IABC-MLP model built in this study is compared with the ABC-MLP and particle swarm optimization (PSO) coupling algorithms. The research shows that IABC can significantly improve the training and prediction accuracy of MLP. Compared with the ABC-MLP and PSO-MLP coupling models, the training accuracy of the IABC-MLP model is increased by 1.6% and 4.5%, respectively. This model is also compared with common individual learning algorithms such as MLP, decision tree (DT), support vector machine regression (SVR), and random forest algorithms (RF). Based on the comparison of prediction results, the proposed method shows excellent performance in all indicators and demonstrates the superiority of heuristic algorithms in predicting the compressive strength of concrete.

Abstract In order to improve the accuracy of concrete dynamic principal identification, a concrete dynamic principal identification model based on Improved Dung Beetle Algorithm (IDBO) optimized Long Short-Term Memory (LSTM) network is proposed. Firstly, the apparent stress–strain curves of concrete containing damage evolution were measured by Split Hopkinson Pressure Bar (SHPB) test to decouple and separate the damage and rheology, and this system was modeled by using LSTM network. Secondly, for the problem of low convergence accuracy and easy to fall into local optimum of Dung Beetle Algorithm (DBO), the greedy lens imaging reverse learning initialization population strategy, the embedded curve adaptive weighting factor and the PID control optimal solution perturbation strategy are introduced, and the superiority of IDBO algorithm is proved through the comparison of optimization test with DBO, Harris Hawk Optimization Algorithm, Gray Wolf Algorithm, and Fruit Fly Algorithm and the combination of LSTM is built to construct the IDBO-LSTM dynamic homeostasis identification model. The final results show that the IDBO-LSTM model can recognize the concrete material damage without considering the damage; in the case of considering the damage, the IDBO-LSTM prediction curves basically match the SHPB test curves, which proves the feasibility and excellence of the proposed method.

Abstract With the popularity of shared bicycles in urban areas, more and more residents choose this fast and convenient mode of transportation for short-distance travel. By optimizing the layout of shared bicycle parking areas and delivery quantity, the investment cost of shared bicycle enterprises can be effectively reduced, and the convenience of residents' travel can be improved at the same time. In this paper, we develop a collaborative optimization model for the layout of the shared bicycle parking area and delivery quantity, aiming at minimizing the walking distance of residents and the investment cost of enterprises, while considering the constraints of the parking area's attractive range and the number of bicycles placed. Aiming at the characteristics of this mixed integer nonlinear problem, an improved genetic algorithm incorporating symmetric individual precision control mechanism is designed. Finally, taking the planned area between the Second Ring Road and the Third Ring Road in the northern part of Jin-niu District, Chengdu as the background, the proposed collaborative optimization model for the layout of shared bicycle parking areas and delivery quantity is applied to a real scene. The results show that after optimization, the number of parking areas is reduced by 2, and the total investment cost is reduced by about 12.2%.

Abstract Abiotic stress is an important factor affecting turf establishment and limiting the sustainability of the turf industry. To alleviate the effects of combined cold and drought stress in cold- and drought-prone regions, it is essential to select and introduce turfgrass germplasms that are suitable for these conditions for successful turf establishment. Thus, we evaluated the effects of combined extreme cold and drought stress on the morphological, plant leaf functional, photosynthetic, and physiological and biochemical traits of 16 wild annual bluegrass (Poa annua) germplasms. We found that there were significant differences (P

Abstract Cancer-associated fibroblasts (CAFs) play a role in ovarian cancer (OV) evolution, immunosuppression and promotion of drug resistance. Exploring the value of CAFs-related biomarker in OV is of great importance. In the present work, we developed a CAFs-related index (CAFRI) based on an integrated analysis of single-cell and bulk RNA-sequencing and highlighted the value of CAFRI in predicting clinical outcomes in individuals with OV, tumour immune microenvironment (TIME) and response to immune checkpoint inhibitors (ICIs). The GSE151214 cohort was used for cell subpopulation localization and analysis, the TCGA-OV patients as a training set. Moreover, the ICGC-OV, GSE26193, GSE26712 and GSE19829 cohorts were used for the validation of CAFRI. The TIMER 2.0, CIBERSORT and ssGSEA algorithms were used for analysis of TIME characteristics based on the CAFRI. The GSVA, GSEA, GO, KEGG and tumour mutation burden (TMB) analyses were used for mechanistic exploration. Additionally, the IMvigor210 cohort was conducted to validate the predictive value of CAFRI on the efficacy of ICIs. Finally, CAFRI-based antitumour drug sensitivity was analysed. The findings demonstrate that the CAFRI can served as an excellent predictor of prognosis for individuals with OV, as well as identifying patients with different TIME characteristics, differentiating between immune ‘hot’ and ‘cold’ tumour populations, and providing new insights into the selection of ICIs and personalised treatment regimens. CAFRI provides new perspectives for the development of novel prognostic and immunotherapy efficacy predictive biomarkers for OV.

Abstract This study explores the analysis and modeling of energy consumption in the context of database workloads, aiming to develop an eco-friendly database management system (DBMS). It leverages vibration energy harvesting systems with self-sustaining wireless vibration sensors (WVSs) in combination with the least square support vector machine algorithm to establish an energy consumption model (ECM) for relational database workloads. Through experiments, the performance of self-sustaining WVS in providing power is validated, and the accuracy of the proposed ECM during the execution of Structured Query Language (SQL) statements is evaluated. The findings demonstrate that this approach can reliably predict the energy consumption of database workloads, with a maximum prediction error rate of 10% during SQL statement execution. Furthermore, the ECM developed for relational databases closely approximates actual energy consumption for query operations, with errors ranging from 1 to 4%. In most cases, the predictions are conservative, falling below the actual values. This finding underscores the high predictive accuracy of the ECM in anticipating relational database workloads and their associated energy consumption. Additionally, this paper delves into prediction accuracy under different types of operations and reveals that ECM excels in single-block read operations, outperforming multi-block read operations. ECM exhibits substantial accuracy in predicting energy consumption for SQL statements in sequential and random read modes, especially in specialized database management system environments, where the error rate for the sequential read model is lower. In comparison to alternative models, the proposed ECM offers superior precision. Furthermore, a noticeable correlation between model error and the volume of data processed by SQL statements is observed. In summary, the relational database ECM introduced in this paper provides accurate predictions of workload and database energy consumption, offering a theoretical foundation and practical guidance for the development of eco-friendly DBMS.

Abstract Prunella vulgaris L. (P. vulgaris) has long been considered to have antipyretic, analgesic and anti-inflammatory effects, lowering blood lipids and pressure. Many studies show that in addition to the traditional telomere attrition, DNA damage and epigenetic changes, immunosenescence is also a new possibility to explore the mechanism of ageing. Therefore, this herb may have potential anti-ageing effects. Typically, there are a series of markers that identify senescent cells, such as superoxide dismutase (SOD)2, an inhibitor of CDK4 (p16INK4A), tumor necrosis factor (TNF)-α, immune cells number, proliferation, and nuclear abnormalities. These changes rarely present in young tissues, while greatly increasing in response to ageing. Firstly, the ageing model of the Institute of Cancer Research (ICR) mouse was established by d-galactose subcutaneous injection. Then, SOD2, p16INK4A and TNF-α were detected by quantitative Real-time PCR (qPCR), Western Blot (WB) and Enzyme-Linked Immunosorbent Assay (ELISA). Simultaneously, senescent cells in livers were stained by hematoxylin and eosin (HE). The viability of splenocytes was detected by Cell Counting Kit-8(CCK-8). The difference in specific immune cells (NK cells, B lymphocytes and T lymphocytes) was detected by flow cytometry. Both low (100 mg/kg) and high (300 mg/kg) concentrations of P. vulgaris treated ageing ICR mice show anti-ageing alterations, such as p16INK4A decreased approximately 1/2 and SOD2 tripled in livers, TNF-α decreased from 1 to 0.6 in plasma, and T cells increased from 0.09 to 0.19%. Compared with the ageing group, the spleen cells in the Prunella-treated group had stronger proliferation ability. Thus, P. vulgaris could have an anti-ageing effect. This is the first study to demonstrate the anti-ageing effect of P. vulgaris. It may also be capable of preventing a variety of age-related diseases.

Abstract ACT001 is a novel sesquiterpene lactone derivative that has been shown to have significant antitumor and anti-inflammatory effects. However, the effect of ACT001 on nonalcoholic steatohepatitis (NASH) is unknown. Methionine and choline deficient (MCD) diet induced NASH model in C57BL/6J mice. Steatosis, inflammation and fibrosis-related indices of serum and liver tissues were detected by fully automated biochemical analyzer, enzyme-linked immunosorbent assay (ELISA) kit, flow cytometry, hematoxylin and eosin (H&E), Masson and immunohistochemical staining. The results showed that ACT001 reduced serum lipid and inflammatory factor levels, attenuated hepatic steatosis, inflammation and fibrosis, and inhibited hepatic oxidative stress and activation of NOD-like receptor protein 3 (NLRP3) inflammatory vesicles in NASH mice. In addition, 381 differentially expressed proteins (DEPs), including 162 up-regulated and 219 down-regulated proteins, were identified in the MCD group and ACT001 high-dose group using isotope labeling relative and absolute quantification (iTRAQ) technique analysis. Among these DEPs, five proteins associated with NAFLD were selected for real-time fluorescence quantitative PCR (RT-qPCR) validation, and the results were consistent with proteomics. In conclusion, ACT001 has a therapeutic effect on NASH, and the results of proteomic analysis will provide new ideas for the mechanism study of ACT001 for NASH treatment.

Abstract Ischemic stroke is highly concerning because it often leads to severe long-term neurological disability. Among clinical trials, ischemic stroke and inflammatory bowel disease interactions have been increasingly reported in recent years. Therefore, using bioinformatics approaches to explore novel protein interactions between them is of interest. We performed this exploratory analysis by using bioinformatics tools such as string to analyze gene data downloaded from NHGRI-GWAS data related to ischemic stroke and inflammatory bowel disease. We constructed a prospective protein interaction network for ischemic stroke and inflammatory bowel disease, identifying cytokine and interleukin-related signaling pathways, Spliceosome, Ubiquitin–Proteasome System (UPS), Thrombus, and Anticoagulation pathways as the crucial biological mechanisms of the network. Furthermore, we also used data-independent acquisition mass spectrometry (DIA-MS) to detect differential protein expression in eight samples, which also suggested that immune system, signal transduction, and hemostasis-related pathways are key signaling pathways. These findings may provide a basis for understanding the interaction between these two states and exploring possible molecular and therapeutic studies in the future.

Abstract Abscisic acid (ABA) is a plant hormone that plays an important role in cotton fiber development. In this study, the physiological changes and proteomic profiles of cotton (Gossypium hirsutum) ovules were analyzed after 20 days of ABA or ABA inhibitor (ABAI) treatment. The results showed that compared to the control (CK), the fiber length was significantly decreased under ABA treatment and increased under ABAI treatment. Using a tandem mass tags-based quantitative technique, the proteomes of cotton ovules were comprehensively analyzed. A total of 7321 proteins were identified, of which 365 and 69 differentially accumulated proteins (DAPs) were identified in ABA versus CK and ABAI versus CK, respectively. Specifically, 345 and 20 DAPs were up- and down-regulated in the ABA group, and 65 and 4 DAPs were up- and down-regulated in the ABAI group, respectively. The DAPs in the ABA group were mainly enriched in the biosynthesis of secondary metabolites, phenylpropanoid biosynthesis and flavonoid secondary metabolism, whereas the DAPs in the ABAI group were mainly enriched in the indole alkaloid biosynthesis and phenylpropanoid biosynthesis pathways. Moreover, 9 proteins involved in phenylpropanoid biosynthesis were upregulated after ABA treatment, suggesting that this pathway might play important roles in the response to ABA, and 3 auxin-related proteins were upregulated, indicating that auxin might participate in the regulation of fiber development under ABAI treatment.

Abstract Polycystic ovary syndrome (PCOS) is associated with adverse pregnancy outcomes, including an increased risk of abortion, premature delivery, and even neonatal outcomes. After removing the effect of COH on patients, studying the pregnancy outcomes of patients with different PCOS phenotypes after FET may better reflect the impact of different PCOS phenotypes on ART outcomes. Data of 8903 patients who underwent FET between January 2017 and October 2019 were retrospectively collected and evaluated. All patients were divided into a control group and four phenotype groups based on Rotterdam criteria. The main outcomes were pregnancy outcomes after FET. We found significantly higher abortion (P = 0.010) and lower ongoing pregnancy (P = 0.023) rates for women with PCOS phenotypes A and D compared to those in the control group. After adjusting for potential confounders, PCOS phenotypes A and D were associated with an elevated risk of abortion (adjusted OR, 1.476, P = 0.016; adjusted OR, 1.348, P = 0.008, respectively). The results of this study suggest that when performing FET, clinicians should individually manage women with PCOS phenotypes A and D to reduce the rate of abortion and increase the rate of LB, and achieve better pregnancy outcomes.

Abstract Endometrial epithelial cells carry distinct cancer-associated alterations that may be more susceptible to endometriosis. Mouse models have shown that overexpression of SIRT1 associated with oncogene activation contributes to the pathogenesis of endometriosis, but the underlying reason remains elusive. Here, we used integrated systems biology analysis and found that enrichment of endometrial stromal fibroblasts in endometriosis and their cellular abundance correlated negatively with epithelial cells in clinical specimens. Furthermore, endometrial epithelial cells were characterized by significant overexpression of SIRT1, which is involved in triggering the EMT switch by escaping damage or oncogene-induced induced senescence in clinical specimens and in vitro human cell line models. This observation supports that genetic and epigenetic incident favors endometrial epithelia cells escape from senescence and fuel EMT process in endometriosis, what could be overcome by downregulation of SIRT1.

Abstract Endometritis is the failure of embryo implantation and an important cause of infertility in dairy cows. IFN-τ is a type I interferon unique to ruminants. In regulating the process of inflammatory response, IFN-τ can be expressed through MicroRNAs (miRNAs) to regulate the process of inflammation. However, IFN-τ regulates lipopolysaccharide (LPS)-induced inflammatory injury of bEECs through the highly conserved miR-26a in mammals, and the mechanism remains unclear. Bovine endometrial epithelial cells (bEECs)were isolated and cultured to establish an inflammatory injury model. RT–qPCR and ELISA were used to detect the secretion of inflammatory factors. Dual-luciferase assays and target gene silencing assays determine the regulatory role of miRNAs. The target protein was detected by immunofluorescence and western blotting. This study showed that the expression of miR-26a was significantly down-regulated in mouse endometrium inflammatory injury tissue and LPS stimulated bEECs; and IFN-τ reversed the expression of miR-26a. The study also showed that the overexpression of miR-26a significantly inhibited the secretion of pro-inflammatory cytokines IL-1β, IL-6 and TNF-α. In addition, studies have shown that miR-26a inhibits its translation by targeting PTEN 3′-UTR, which in turn activates the Phosphatidylinositide 3-kinases/protein kinase B (PI3K/AKT) pathway, so that nuclear factor kappa-B (NF-κB) signaling is inhibited. In summary, the results of this study further confirm that IFN-τ as an anti-inflammatory agent can up-regulate the expression of miR-26a and target the PTEN gene to inhibit the inflammatory damage of bEECs.

Abstract A large-scale sand liquefaction producing typical and novel surface phenomena was found at the epicenter of Songyuan M5.7 earthquake occurring on May 28, 2018. Field survey and experimental test encompassing boring sampling, standard penetration test (SPT), cone penetration test (CPT), scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray fluorescence (XRF) were performed to ascertain the liquefaction damage and site characteristic. Cone penetration test is an excellent assay for the identification of liquefied sand layer and acquisition of physio-mechanical parameter. Moreover, the assay is applicable for in-situ post-earthquake investigation. Factors promoting the formation and controlling the distribution of the sand liquefaction were analyzed. The liquefaction impacted an 80 km2 area, and was primarily embodied as sand boil and water sprout on rice field, despite producing no significant structural damage. Due to the simple profile of local soil layer, ground motion, geomorphic condition, and groundwater level were the main factors governing the distribution of the liquefaction. Majority of the liquefied sand layer was discovered at the depth less than 10 m. However, deep layer liquefaction at the depth greater than 18 m was also discovered, which was demonstrated by the upward movement of liquefied sand towards the upper silty clay layer at the depth of 17 m. Most importantly, we have identified loess liquefaction, a phenomenon which had not been reported previously in Northeast China. Lastly, it is important to highlight the risk of significant liquefaction damage at Songyuan. Hence, investigating the liquefaction risk is potentially beneficial for augmenting planning on earthquake mitigation, engineering reconnaissance, and design project.

Abstract To investigate the feasibility of using ICAM-1-targeted nano ultrasonic contrast to evaluate the degree of inflammatory injury at different stages in the abdominal aorta of rabbits with atherosclerosis (AS). Twenty-five experimental rabbits were assigned to five groups: the control group (A); the week-4 after modeling group (B); the week-8 after modeling group (C); the week-12 after modeling group (D); the week-16 after modeling group (E). All groups were given 2D ultrasonography, conventional ultrasonic contrast (SonoVue), and ICAM-1-targeted nano ultrasonic contrast, respectively. Signal intensity of vascular perfusion was evaluated. Signal intensity of ICAM-1-targeted nano ultrasonic contrast was substantially enhanced and prolonged in the vascular wall of the abdominal bubble aorta increased in B, C, D, and E groups (all P

Abstract No FDA approved pharmacological therapy is available to reduce neuroinflammation following heatstroke. Previous studies have indicated that dexmedetomidine (DEX) could protect against inflammation and brain injury in various inflammation-associated diseases. However, no one has tested whether DEX has neuro-protective effects in heatstroke. In this study, we focused on microglial phenotypic modulation to investigate the mechanisms underlying the anti-inflammatory effects of DEX in vivo and in vitro. We found that DEX treatment reduced the expression of CD68, iNOS, TNF-α, and IL-1β, and increased the expression of CD206, Arg1, IL-10 and TGF-β in microglia, ameliorating heatstroke induced neuroinflammation and brain injury in mice. TREM2, whose neuro-protective function has been validated by genetic studies in Alzheimer’s disease and Nasu-Hakola disease, was significantly promoted by DEX in the microglia. TREM2 esiRNA reversed the DEX-induced activation of PI3K/Akt signalling. Overall these findings indicated that DEX may serve, as a potential therapeutic approach to ameliorate heatstroke induced neuroinflammation and brain injury via TREM2 by activating PI3K/Akt signalling.

Abstract Xenotransplantation (cross-species transplantation) using genetically-engineered pig organs offers a potential solution to address persistent organ shortage. Current evaluation of porcine genetic modifications is to monitor the nonhuman primate immune response and survival after pig organ xenotransplantation. This measure is an essential step before clinical xenotransplantation trials, but it is time-consuming, costly, and inefficient with many variables. We developed an efficient approach to quickly examine human-to-pig xeno-immune responses in vitro. A porcine endothelial cell was characterized and immortalized for genetic modification. Five genes including GGTA1, CMAH, β4galNT2, SLA-I α chain, and β2-microglobulin that are responsible for the production of major xenoantigens (αGal, Neu5Gc, Sda, and SLA-I) were sequentially disrupted in immortalized porcine endothelial cells using CRISPR/Cas9 technology. The elimination of αGal, Neu5Gc, Sda, and SLA-I dramatically reduced the antigenicity of the porcine cells, though the cells still retained their ability to provoke human natural killer cell activation. In summary, evaluation of human immune responses to genetically modified porcine cells in vitro provides an efficient method to identify ideal combinations of genetic modifications for improving pig-to-human compatibility, which should accelerate the application of xenotransplantation to humans.

Abstract Although many putative long non-coding RNA (lncRNA) genes have been identified in insect genomes, few of these genes have been functionally validated. A screen for female-specific larvicides that facilitate Aedes aegypti male sex separation uncovered multiple interfering RNAs with target sites in lncRNA genes located in the M/m locus region, including loci within or tightly linked to the sex determination locus. Larval consumption of a Saccharomyces cerevisiae (yeast) strain engineered to express interfering RNA corresponding to lncRNA transcripts resulted in significant female death, yet had no impact on male survival or fitness. Incorporation of the yeast larvicides into mass culturing protocols facilitated scaled production and separation of fit adult males, indicating that yeast larvicides could benefit mosquito population control strategies that rely on mass releases of male mosquitoes. These studies functionally verified a female-specific developmental requirement for M/m locus region lncRNA genes, suggesting that sexually antagonistic lncRNA genes found within this highly repetitive pericentromeric DNA sequence may be contributing to the evolution of A. aegypti sex chromosomes.

Abstract Prunus mume (also known as Mei) is an important ornamental plant that is popular with Asians. The weeping trait in P. mume has attracted the attention of researchers for its high ornamental value. However, the formation of the weeping trait of woody plants is a complex process and the molecular basis of weeping stem development is unclear. Here, the morphological and histochemical characteristics and transcriptome profiles of upright and weeping stems from P. mume were studied. Significant alterations in the histochemical characteristics of upright and weeping stems were observed, and the absence of phloem fibres and less xylem in weeping stems might be responsible for their inability to resist gravity and to grow downward. Transcriptome analysis showed that differentially expressed genes (DEGs) were enriched in phenylpropanoid biosynthesis and phytohormone signal transduction pathways. To investigate the differential responses to hormones, upright and weeping stems were treated with IAA (auxin) and GA3 (gibberellin A3), respectively, and the results revealed that weeping stems had a weaker IAA response ability and reduced upward bending angles than upright stems. On the contrary, weeping stems had increased upward bending angles than upright stems with GA3 treatment. Compared to upright stems, interestingly, DEGs associated with diterpenoid biosynthesis and phenylpropanoid biosynthesis were significantly enriched after being treated with IAA, and expression levels of genes associated with phenylpropanoid biosynthesis, ABC transporters, glycosylphosphatidylinositol (GPI)—anchor biosynthesis were altered after being treated with GA3 in weeping stems. Those results reveal that multiple molecular mechanisms regulate the formation of weeping trait in P. mume, which lays a theoretical foundation for the cultivation of new varieties.

Abstract Vaginitis is very common among women, especially women of childbearing age, and is associated with significantly increased risk of preterm birth and pelvic inflammatory diseases. An imbalance in the vaginal flora, the primary cause of vaginitis, promotes the initiation and progression of vaginal infections. However, the responsible mechanisms are still poorly understood. Using a murine vaginitis model of Escherichia coli infection, we demonstrated that decreased expression of microRNA1976 and increased expression of CD105 and integrin αvβ6 were closely associated with the progression of vaginal infection. Importantly, we demonstrated for the first time that the microRNA1976/CD105/integrin αvβ6 axis regulates E. coli-mediated vaginal infection in mice, as evidenced by the finding that E. coli-induced vaginal infection was reversed by microRNA1976 overexpression and exacerbated by CD105 overexpression. The regulation of CD105 and integrin αvβ6 by microRNA1976 was further confirmed in a murine model of vaginitis with adenoviral vector treatment. Taken together, our data suggested that microRNA1976 negatively regulates E. coli-induced vaginal infection in mice at least in part by suppressing CD105 and integrin αvβ6 expression. These findings may provide new insight into the mechanisms of E. coli-induced vaginitis, identify a novel diagnostic biomarker and a potential therapeutic target for flora imbalance-associated vaginitis.

Abstract Carbon starvation is the current leading hypothesis of plant mortality mechanisms under drought stress; recently, it is also used to explain tree die-off in plant diseases. However, the molecular biology of the carbon starvation pathway is unclear. Here, using a punch inoculation system, we conducted transcriptome and physiological assays to investigate pathogen response in poplar stems at the early stages of Botryosphaeria and Valsa canker diseases. Transcriptome assays showed that the majority of differentially expressed genes (DEGs) in stem phloem and xylem, such as genes involved in carbon metabolism and transportation, aquaporin genes (in xylem) and genes related to the biosynthesis of secondary metabolites and the phenylpropanoid pathway (related to lignin synthesis), were downregulated at 7 days after inoculation (DAI). Results also showed that the expression of the majority of disease-resistance genes upregulated in poplar stems, which may be connected with the downregulation expression of the majority of WRKY family genes. Physiological assays showed that transpiration rate decreased but WUE (water use efficiency) increased the 3 and 7 DAI, while the net photosynthetic rate decreased at 11 DAI in Botryosphaeria infected poplars (ANOVA, P

Abstract The aim of this study was to investigate the use of de-blooming algorithm in coronary CT angiography (CCTA) for optimal evaluation of calcified plaques. Calcified plaques were simulated on a coronary vessel phantom and a cardiac motion phantom. Two convolution kernels, standard (STND) and high-definition standard (HD STND), were used for imaging reconstruction. A dedicated de-blooming algorithm was used for imaging processing. We found a smaller bias towards measurement of stenosis using the de-blooming algorithm (STND: bias 24.6% vs 15.0%, range 10.2% to 39.0% vs 4.0% to 25.9%; HD STND: bias 17.9% vs 11.0%, range 8.9% to 30.6% vs 0.5% to 21.5%). With use of de-blooming algorithm, specificity for diagnosing significant stenosis increased from 45.8% to 75.0% (STND), from 62.5% to 83.3% (HD STND); while positive predictive value (PPV) increased from 69.8% to 83.3% (STND), from 76.9% to 88.2% (HD STND). In the patient group, reduction in calcification volume was 48.1 ± 10.3%, reduction in coronary diameter stenosis over calcified plaque was 52.4 ± 24.2%. Our results suggest that the novel de-blooming algorithm could effectively decrease the blooming artifacts caused by coronary calcified plaques, and consequently improve diagnostic accuracy of CCTA in assessing coronary stenosis.

Abstract The current study compared the effectiveness of distraction, an antecedent-focused strategy that involves diverting an individual’s attention away from affective terms, and expressive suppression, a response-focused strategy that involves inhibiting conscious emotion-expressive behavior during an emotionally aroused state, in the regulation of high- and low-intensity unpleasant stimuli, using event-related potentials (ERPs). Sixteen participants completed an emotion regulation experiment in which they passively viewed high- or low-intensity unpleasant images (view), solved a mathematical equation presented on high- or low-intensity negative images (distraction), or suppressed their emotional expression in response to high- or low-intensity unpleasant images (suppression). Their negative experiences after implementation of these strategies were rated by participants on a 1–9 scale. We mainly found that compared with expressive suppression, distraction yielded greater attenuation of the early phase of centro-parietal LPP when the participants responded to high-intensity stimuli. In the low-intensity condition, distraction, but not expressive suppression, effectively decreased the early phase of LPP. The findings suggest that expressive suppression works as early as distraction in the high-intensity condition; more importantly, distraction is superior to expressive suppression in regulating negative emotion, which is influenced by emotional intensity.

Abstract Detection of autoantibodies in systemic lupus erythematosus (SLE) plays an important role in timely diagnosis and earlier treatment of SLE. In this study, we used a SmD1 polypeptide-based ELISA to determine anti-SmD1 antibody in 269 SLE, including100 naïve (had not been treated with steroids or immunosuppressants at study inception) SLE patients and 169 non-naive SLE patients; 233 controls with other rheumatic diseases (RDC) (70 RA, 40 AS, 73SSc, and 50 SS), and 110 healthy controls (HC) group. The positive rate of anti-SmD1 among all SLE patients was 60.97%, higher than that in the RDC group (13.30%, P = 0.000) or the HC group (9.09%, P = 0.000). The positive rate of anti-SmD1 in non-naive SLE patients was higher than that for anti-dsDNA antibodies (44.97%, P = 0.03). Positivity for anti-SmD1 only was found in 14.00% of naive SLE patients and 16.00% of non-naive SLE patients. In naive SLE patients, the serum concentration of anti-SmD1 was lower after treatment than before treatment (P = 0.039). Active SLE patients positive for anti-SmD1 were more likely to have malar rash, rash, nonscarring alopecia, PAH and hypocomplementemia. High positivity for anti-SmD1 only in patients with SLE indicated the importance and necessity of detection of anti-SmD1 in patients with SLE.

Abstract Nitrogen (N) is essential for the growth of algae, and its concentration varies greatly in the ocean, which has been regarded as a limitation for phytoplankton growth. Despite its great importance, most of the existing studies on the mechanisms underlying the effects of N on diatoms have focused on physiology, biochemistry and a few target genes and have rarely involved whole genomic analyses. Therefore, in this study, we integrated physiological data with RNA and protein profiling data to reveal the response strategy of Thalassiosira pseudonana under N-depleted conditions. Physiological measurements indicated that the cell growth capacity and chlorophyll content of the cells decreased, as did the expression of photosynthesis- and chlorophyll biosynthesis-related genes or proteins. The RNA-Seq profile results showed that T. pseudonana responded to N deprivation through increases in glycolysis, the TCA cycle and N metabolism as well as down-regulation in the Calvin cycle, gluconeogenesis, pentose phosphate, oxidative phosphorylation and lipid synthesis. These results provide a basic understanding for further research addressing how N affects phytoplankton in terms of genomics.

Abstract This study aimed to provide insights into the relationship between lipid levels and new-onset diabetes (NOD) in 14,864 Chinese hypertensive patients without diabetes (6056 men and 8808 women) aged 45–75 years from the China Stroke Primary Prevention Trial (CSPPT, led by Nanfang Hospital, Guangzhou, China). NOD (defined as fasting plasma glucose (FPG) ≥ 7.0 mmol/L at the end of study or self-reported physician diagnosis of diabetes or self-reported use of hypoglycemic agents during follow-up) was analyzed using multivariate analysis. Follow-up was censored on August 24, 2014. Among the 14,864 subjects, 1615 developed NOD (10.9%, men = 10.8% and women = 10.9%). Increased triglycerides (TG) [odds ratio (OR) = 1.18; 95% confidence interval (CI): 1.13–1.25, P

Abstract SUN1, a component of the LINC (Linker of Nucleoskeleton and Cytoskeleton) complex, functions in mammalian mRNA export through the NXF1-dependent pathway. It associates with mRNP complexes by direct interaction with NXF1. It also binds to the NPC through association with the nuclear pore component Nup153, which is involved in mRNA export. The SUN1-NXF1 association is at least partly regulated by a protein kinase C (PKC) which phosphorylates serine 113 (S113) in the N-terminal domain leading to reduced interaction. The phosphorylation appears to be important for the SUN1 function in nuclear mRNA export since GFP-SUN1 carrying a S113A mutation was less efficient in restoring mRNA export after SUN1 knockdown as compared to the wild type protein. By contrast, GFP-SUN1-S113D resembling the phosphorylated state allowed very efficient export of poly(A)+RNA. Furthermore, probing a possible role of the LINC complex component Nesprin-2 in this process we observed impaired mRNA export in Nesprin-2 knockdown cells. This effect might be independent of SUN1 as expression of a GFP tagged SUN-domain deficient SUN1, which no longer can interact with Nesprin-2, did not affect mRNA export.

Abstract The sorption mechanism of nickel (Ni) at the illite/water interface was investigated using batch, sorption modelling, extended X-ray absorption fine structure (EXAFS), and extraction approaches. The results showed that Ni(II) sorption on illite was strongly dependent on pH, contact time, temperature, and initial Ni(II) concentration. At a low initial Ni(II) concentration, the ion exchange species of ≡X2Ni° and the inner-sphere complexes including ≡SsONi+, ≡SwONi+ and ≡SwONiOH° species are observed on the sorption edges of Ni(II) on illite. As the initial Ni(II) concentration increased to 1.7 × 10−3 mol/L, precipitates including surface-induced precipitation of s-Ni(OH)2 and amorphous Ni(OH)2 became more significant, especially under neutral to alkaline conditions. EXAFS analysis confirmed that Ni-Al layered double hydroxide (LDH) can gradually form with an increase in the contact time. At pH 7.0, α-Ni(OH)2 was produced in the initial stage and then transformed to the more stable form of Ni-Al LDH with increasing contact time because of the increased Al3+ dissolution. With an increase in temperatures, α-Ni(OH)2 phase on illite transformed to Ni-Al LDH phase, indicating a lower thermodynamic stability compared to Ni-Al LDH phase. These results are important to understand the geochemical behaviors to effectively remediate soil contaminated with Ni(II).

Abstract Traumatic brain injury-induced acute lung injury (TBI-ALI) is a serious complication after brain injury for which predictive factors are lacking. In this study, we found significantly elevated blood glutamate concentrations in patients with TBI or multiple peripheral trauma (MPT), and patients with more severe injuries showed higher blood glutamate concentrations and longer durations of elevated levels. Although the increase in amplitude was similar between the two groups, the duration was longer in the patients with TBI. There were no significant differences in blood glutamate concentrations in the patients with MPT with regard to ALI status, but the blood glutamate levels were significantly higher in the patients with TBI-ALI than in those without ALI. Moreover, compared to patients without ALI, patients with TBI showed a clearly enhanced inflammatory response that was closely correlated with the blood glutamate levels. The blood glutamate concentration was also found to be a risk factor (adjusted odds ratio, 2.229; 95% CI, 1.082–2.634) and was a better predictor of TBI-ALI than the Glasgow Coma Scale (GCS) score. These results indicated that dramatically increased blood glutamate concentrations were closely related to the occurrence of TBI-ALI and could be used as a predictive marker for “at-risk” patients.

Abstract Adequately understanding band inversion mechanism, one of the significant representations of topological phase, has substantial implications for design and regulation of topological insulators (TIs). Here, by identifying an unconventional band inversion, we propose an intrinsic quantum spin Hall (QSH) effect in iodinated group-V binary (ABI2) monolayers with a bulk gap as large as 0.409 eV, guaranteeing its viable application at room temperature. The nontrivial topological characters, which can be established by explicit demonstration of Z2 invariant and gapless helical edge states, are derived from the band inversion of antibonding states of p x,y orbitals at the K point. Furthermore, the topological properties are tunable under strain engineering and external electric field, which supplies a route to manipulate the spin/charge conductance of edge states. These findings not only provide a new platform to better understand the underlying origin of QSH effect in functionalized group-V films, but also are highly desirable to design large-gap QSH insulators for practical applications in spintronics.

Abstract Strictosidine synthase (STR) plays an important role in the biosynthesis of terpenoid indole alkaloids (TIAs) and is expressed in a range of active meristematic tissues of higher plants. STR proteins are involved in different physiological and biochemical pathways. However, the function of STR proteins in rice development remains poorly understood. In this study, we identified 21 possible STR-like (OsSTRL) family members in rice genome and found that only one gene, OsSTRL2, exhibited a pre-emergency specific florescence expression pattern. Tissue-specific expression profile analysis, β-glucuronidase histochemical (GUS) staining and RNA in situ hybridization confirmed that OsSTRL2 was highly expressed in tapetal cells and microspores. Comparative protein sequence analysis indicated that OsSTRL2 lacked the key catalytic residue found in a typical STR (STR1), although it possessed conserved β-propellers and α-helices formed the basic structure of STR1. OsSTRL2 knockout mutant resulted to male sterility because of the defects in anther development and pollen wall formation. Subcellular localization of OsSTRL2-YFP revealed that the OsSTRL2 protein was primarily localized in the endoplasmic reticulum (ER). Therefore, OsSTRL2 is an atypical strictosidine synthase that plays crucial roles in regulating anther development and pollen wall formation in rice.

Abstract The gastrointestinal tract is responsible for food digestion and absorption. The muscularis propria propels the foodstuff through the GI tract and defects in intestine motility may cause obstruction disorders. Our present genetic studies identified non-receptor tyrosine kinase c-Abl as an important regulator of the muscularis propria homeostasis and a risk factor for rectal prolapse. Mouse deficient for c-Abl showed defects in the muscularis propria of gastrointestinal tract and older c-Abl −/− mice developed megaesophagus and rectal prolapse. Inhibition of c-Abl with imatinib mesylate, an anti-CML drug, or ablation of c-Abl using Prx1-Cre, which marks smooth muscle cells, recapitulated most of the muscularis propria phenotypes. The pathogenesis of rectal prolapse was attributable to overproliferation of smooth muscle cells, which was caused by enhanced ERK1/2 activation. Administration of ERK inhibitor U0126 impeded the development of rectal prolapse in c-Abl deficient mice. These results reveal a role for c-Abl-regulated smooth muscle proliferation in the pathogenesis of rectal prolapse, and imply that long-term use of imatinib mesylate may cause gastrointestinal problems in patients while ERK inhibitor may be effective in treating rectal prolapse.

Abstract Traumatic brain injury (TBI) can induce cognitive dysfunction due to the regional accumulation of hyperphosphorylated tau protein (p-tau). However, the factors that cause p-tau to concentrate in specific brain regions remain unclear. Here, we show that AQP4 polarization in the perivascular astrocytic end feet was impaired after TBI, which was most prominent in the ipsilateral brain tissue surrounding the directly impacted region and the contralateral hippocampal CA1 area and was accompanied by increased local p-tau, changes in dendritic spine density and morphology, and upregulation of the adenosine A2A receptor (A2AR). The critical role of the A2AR signaling in these pathological changes was confirmed by alleviation of the impairment of AQP4 polarity and accumulation of p-tau in the contralateral CA1 area in A2AR knockout mice. Given that p-tau can be released to the extracellular space and that the astroglial water transport via AQP4 is involved in tau clearance from the brain interstitium, our results suggest that regional disruption of AQP4 polarity following TBI may reduce the clearance of the toxic interstitial solutes such as p-tau and lead to changes in dendritic spine density and morphology. This may explain why TBI patients are more vulnerable to cognitive dysfunction.

Abstract The indirect interactions between insect vectors, such as whiteflies, and the viruses they transmit, such as begomoviruses, via host plants may produce a range of outcome depending on the species/strain of each of the three organisms involved, and the mechanisms underlying the variations are not well understood. Here, we observed the performance of whiteflies on three types of tomato, which vary in level of jasmonic acid (JA)-related resistance and were either uninfected or infected by a begomovirus, to investigate the role of JA-related resistance in mediating whitefly-begomovirus interactions. Compared to the performance of whiteflies on plants of the wild type, the performance was elevated on plants deficient in JA-related resistance but reduced on plants with a high level of JA-related resistance. Further, on plants with a high level of JA-related resistance, the whitefly performed better on virus-infected than on uninfected plants; however, on tomato plants deficient in JA-related resistance, whitefly performance was less affected by the virus-infection of plants. Additionally, the expression of the JA-regulated defense gene PI-II in tomato plants was repressed by virus infection. These findings suggest that JA-related resistance plays an important role in the tripartite interactions between whitefly, begomovirus and tomato plant.

Abstract In this study, the chloride ion (Cl−) binding rate of sulfoaluminate cement (SAC) mortars containing different mineral admixtures was investigated. This is essential to improve the durability of concrete structures in high Cl− environments, especially where they are susceptible to Cl− attack such as coastlines and marine structures. The effects of Cl− concentration, curing age, and the type and amount of mineral admixture on the Cl− binding rate of SAC mortars were analyzed. It was found that the content of water-soluble Cl− in SAC mortars decreased with the increase of curing age, while the Cl− binding ratio increased accordingly, indicating that its resistance to internal Cl− permeation increased. The addition of fly ash (FA) and ground granulated blast furnace slag (GGBS) can significantly improve the Cl− binding rate of SAC mortars, and the Cl− binding rate increases to 46.6% with 20% of FA and 38.7% with 40% of GGBS. The effects of mineral admixtures on the microstructure and phase composition of SAC mortars were further investigated by X-ray diffraction (XRD) analysis. The results showed that the addition of FA and GGBS promoted the formation of C-S-H (calcium silicate hydrate) gels and improved the resistance of SAC mortars to Cl− penetration. On the other hand, the excessive addition of silica fume (SF) decreased the Cl− binding rate, whereas a moderate amount of limestone powder (LP) improved the Cl− binding rate. The study of the Cl− binding rate of SAC mortars can help to evaluate their resistance to Cl− erosion in real projects, thus guiding the optimization of concrete formulations and the improvement of durability.